On the use of the Price equation

This paper distinguishes two categories of questions that the Price equation can help us answer. The two different types of questions require two different disciplines that are related, but nonetheless move in opposite directions. These disciplines are probability theory on the one hand and statistical inference on the other. In the literature on the Price equation this distinction is not made. As a result of this, questions that require a probability model are regularly approached with statistical tools. In this paper, we examine the possibilities of the Price equation for answering questions of either type. By spending extra attention on mathematical formalities, we avoid the two disciplines to get mixed up. After that, we look at some examples, both from kin selection and from group selection, that show how the inappropriate use of statistical terminology can put us on the wrong track. Statements that are 'derived' with the help of the Price equation are, therefore, in many cases not the answers they seem to be. Going through the derivations in reverse can, however, be helpful as a guide how to build proper (probabilistic) models that do give answers.     

The state of the art in the analysis of two-dimensional gel electrophoresis images

Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field. An erratum to this article can be found at     

European-wide GIS-based modelling system for quantifying the feedstock from Miscanthus and the potential contribution to renewable energy targets

Reliable estimates of feedstock resources are a prerequisite to the establishment of a biomass based-industry for energy and non food products. Field trials in the European Union (EU) show that Miscanthus spp. can produce high yields. Here we use a model (MISCANMOD) coupled with a GIS environment to estimate the contribution that Miscanthus could make to projected national electricity consumption. We describe the integration of different data sets, transformation procedures, and spatial analyses using GIS to produce energy statistics for the EU-25. Overall, Miscanthus grown on the 10% of arable land which is currently in set-aside could generate 282 TWh yr⁻¹ electricity. This would meet 39% of the EU-25 target of 723 TWh yr⁻¹ of electricity from renewable energy sources (RES) by 2010. As RES targets rise, land available for energy crops is also expected to increase. We consider three additional scenarios where Miscanthus could be grown on 10%, 20% and 35% of all agricultural land and we estimate it could generate respectively 345, 691 and 1209 TWh yr⁻¹ of electrical energy. At a national scale France, Poland and Germany have the highest potentials for Miscanthus production based on agricultural land area (respectively 83, 52, 49 TWh yr⁻¹ when 10% agricultural land is used). Finally, we reduced the scale to the EU NUTS2 (Nomenclature of Territorial Units for Statistics) regions to examine regional generation capacities. Key regions have been identified where national RES targets are exceeded. These regions could become net exporters of renewable energy.     

Subpopulation distribution of motile sperm relative to activation medium in steelhead (Oncorhynchus mykiss)

In the present study, steelhead sperm were activated in artificial tap water, ovarian fluid, activating saline, or in combinations of these media, and motility characteristics were determined using computer-assisted sperm analysis. Motility characteristics of individual sperm were then assessed to test the hypothesis that motile sperm are distributed among discrete subpopulations and that their distribution is influenced by the activation medium. Analysis with k-means clustering detected three discrete motile sperm subpopulations in steelhead semen, regardless of the activation medium. Based on multivariate analysis of variance, proportions of these subpopulations did not differ between sperm activated with ovarian fluid and activating saline, or any combination of these two media. However, subpopulation distributions for sperm activated with either ovarian fluid or activating saline were influenced by the level of dilution of these media in artificial tap water. There was an increase in the number of sperm in high velocity (curvilinear), high straightness, and high wobble subpopulation with increased levels of ovarian fluid or activating saline. The change in sperm motility characteristics with a change in activation medium may play a role in normal fertilization, as discharged sperm pass from seminal plasma and water through ovarian fluid en route to the egg.     

四川分布的中国种子植物特有科属研究

对传统“特有”概念作了补充说明,确认四川有中国种子植物特有类群129属,12个特有科,在国产特有类群中占有较大比例。生活型虽然以草本为主,但高比例（近1／3）的木本类型以及木本类型多为原始的古特有成分却反映出植物区系的古老性和悠久发展历史。地理分布以盆地四周山地最丰富,西部高原和盆地中部缺乏或少有特有科、属。总体上可划分为3个分布中心区,包括西南区、东南区和东北区。新特有成分以西南区较多,而古特有成分大多集中中东南区和东北区。特有属与邻近地区的相似性还反映了四川植物区系和邻近地区植物区系的整体性。丰富的特有科、属同时也反映出四川种子植物区系的多样性。     

Discovering Precise Temporal Patterns in Large-Scale Neural Recordings through Robust and Interpretable Time Warping

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Stratified or Multicentre Analysis with Extended Mantel–Haenszel Statistics

Since its introduction in 1959 the ability of the classical Mantel-Haenszel (M–H) procedure for combining the odds ratios of a set of I 2 × 2 tables has led to its use also in stratified or multicentre type clinical trials. A familiar application is the M–H logrank test in survival analysis. An extension of the M–H procedure covering the case of 2 × K contingency tables (MANTEL , 1963) with ordered levels retains the essential property of pooling the results of I homogeneous tables (i.e. in absence of qualitative interactions). The assignment of some score for the K columns of a table is essential for the use of the method (in comparing 2 treatments). Some possibilities of score assignment are discussed: for clinical outcome variables such as the degree of severity of a disease, pain and so on, the score is at hand in a natural way. A less well-known type of scoring consists in ranking the observations of a continuous variable, leading to cell sizes of 1 or 0. In this case, however, if equidistant ranking was used, the E–M–H procedure appears as an extension of Wilcoxon's rank sum test and represents a powerful non-parametric approach in stratified or multicentre type designs with non normally distributed outcome variables. The results of some Monte-Carlo simulations for 2 possible equidistant ranking procedures are presented, which indicate only a moderate gain in power as compared to Wilcoxon's rank sum test under the common situation of centre effects not exceeding treatment effects. Use of the E–M–H pro?edure is also recommended as a simple method to overcome the potential bias due to unequally distributed prognostic factors among treatment groups.     

Some model based considerations on observing generation times for communicable diseases

The generation time of an infectious disease is usually defined as the time from the moment one person becomes infected until that person infects another person. The concept is similar to “generation gap” in demography, with new infections replacing births in a population. Originally applied to diseases such as measles where at least the first generations are clearly discernible, the concept has recently been extended to other diseases, such as influenza, where time order of infections is usually much less apparent.By formulating the relevant statistical questions within a simple yet basic mathematical model for infection spread, it is possible to derive theoretical properties of observations in various situations e.g. in “isolation”, in households, or during large outbreaks. In each case, it is shown that the sampling distribution of observations depends on a number of factors, usually not considered in the literature and that must be taken into account in order to achieve unbiased inference about the generation time distribution. Some implications of these findings for statistical inference methods in epidemic spread models are discussed.